A spotlight on Vaclav: OUAnalyseKMi Reporter, Wednesday 28 July 2021 | Annotate
This week the spotlight shines on Vaclav Bayer who is a Full-Stack Developer in our Learning Analytics Team. Watch this video to hear Vaclav explaining his work.
What can you tell us about your research?
UniversitiesUK and AdvanceHE reports show a 13% degree-awarding gap for Black, Asian and Minority ethnicity students in the UK. Similar issues are found for female and disabled students.
What does it mean in practice?
There is evidence that Black, Asian and Minority Ethnic (BAME) students at the Open University put more effort and spend more time studying, they are, however, less likely to complete, pass or achieve an excellent grade compared to White students.
My research aims to address these awarding gaps in Higher Education. I will use state-of-art Learning Analytics methods for doing so.
What exactly are you researching?
I am currently looking into KMi award-winning project OUAnalyse. It’s a Learning Analytics Predictive system that provides the tutors at The Open University with predictions on students’ success in submitting their upcoming assignments. The predictions help tutors to target in-time and cost-effective interventions. I am investigating if the generated predictions are fair and accurate for all students equally, and if not, what are the reasons and how we can avoid them.
Why is this important?
Awarding gaps translate into socio-economic gaps and further inequalities. Educated people are less dependent on public aid and are more resistant to economic downturns.
In terms of Learning Analytics predictions, we have evidence that the use of the predictions increases the students’ chances to pass the module by 7%. However, if students are wrongly predicted that they will submit their upcoming assignment, but, they don’t manage to submit it, the tutors will most likely miss the opportunity to provide the required support.
What have you learned that you did not expect to?
This type of research made me realise how combining qualitative and quantitative approaches is important as everything cannot be sometimes done by only one approach. Especially when we talk about the awarding gap mitigation, it may take years to evaluate the steps taken to reduce the gaps.
Thank you, Vaclav